Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/1275
Title: Neural network based inspection of voids and karst conduits in hydro-electric power station tunnels using GPR
Authors: Kilic, Gokhan
Eren, Levent
Keywords: GPR
TBM
NDT
Karst conduits
Neural network
Concrete
Sites
Radar
Publisher: Elsevier Science Bv
Abstract: This paper reports on the fundamental role played by Ground Penetrating Radar (GPR), alongside advanced processing and presentation methods, during the tunnel boring project at a Dam and Hydro -Electric Power Station. It identifies from collected GPR data such issues as incomplete grouting and the presence of karst conduits and voids and provides full details of the procedures adopted. In particular, the application of collected GPR data to the Neural Network (NN) method is discussed. (C) 2018 Elsevier B.V. All rights reserved.
URI: https://doi.org/10.1016/j.jappgeo.2018.02.026
https://hdl.handle.net/20.500.14365/1275
ISSN: 0926-9851
1879-1859
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Files in This Item:
File SizeFormat 
304.pdf
  Restricted Access
6.02 MBAdobe PDFView/Open    Request a copy
Show full item record



CORE Recommender

SCOPUSTM   
Citations

44
checked on Nov 20, 2024

WEB OF SCIENCETM
Citations

37
checked on Nov 20, 2024

Page view(s)

78
checked on Nov 18, 2024

Download(s)

6
checked on Nov 18, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.